What is the main difference between Dify, FastGPT, and Coze?

Dify is usually evaluated as a workflow and app-building platform for LLM products, FastGPT is commonly compared for knowledge-base and RAG assistant workflows, and Coze is often considered when users want a bot-building environment with packaged channels and simpler assistant setup.

Which tool is better for RAG knowledge-base agents?

FastGPT and Dify are the strongest comparison points for RAG knowledge-base agents. FastGPT is often attractive for direct knowledge-base assistant work, while Dify is useful when the RAG flow also needs broader workflow orchestration and app logic.

Should I choose Dify or FastGPT for a knowledge-base assistant?

Choose FastGPT when the primary job is a focused knowledge-base assistant with direct RAG setup. Choose Dify when the assistant also needs multi-step workflows, app logic, integrations, or broader LLM product orchestration around retrieval.

When should a builder consider OpenClaw instead?

OpenClaw is worth considering when the project is closer to a personal AI assistant framework or multi-tool assistant architecture rather than a narrow no-code knowledge-base bot.

What should you compare before choosing an AI agent tool?

Compare data-source support, retrieval quality, workflow control, deployment path, pricing, channel integrations, logging, and how easily the tool can be tested against real assistant tasks instead of demos.

Best AI Agent Tools 2026: Dify vs FastGPT vs Coze for RAG

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Mainstream Open Source AI Knowledge Base Tools Review: FastGPT, Dify, Coze

Introduction

Against the backdrop of rapid development in AI applications today, various AI knowledge base tools are emerging constantly, offering rich functionality and application scenarios. This article focuses on three mainstream AI knowledge base tools—FastGPT, Dify, and Coze—evaluating their performance in terms of features, usability, subscription models, and market overview to help developers quickly choose the most suitable tool.

What is RAG?

RAG, short for Retrieval-Augmented Generation, is an AI model that combines retrieval and generation. By referencing information from external knowledge bases, RAG models generate content with higher accuracy and interpretability. This technology was first proposed by the Facebook AI Research team in 2020 and has been widely applied to natural language processing tasks such as question-answering systems, document generation, and intelligent assistants. The core advantage of RAG models lies in their versatility, enabling real-time knowledge updates and providing efficient, accurate information services through end-to-end evaluation methods.

RAG also has the capability to optimize outputs from large language models (LLMs), allowing them to reference domain-specific knowledge bases without retraining, thereby improving the relevance and reliability of generated content. RAG models build data structures through indexing for efficient retrieval, then retrieve from external knowledge bases based on user queries, and finally integrate the query content to generate responses. This workflow makes RAG a flexible knowledge base management solution, suitable for knowledge integration needs in chatbots and other conversational systems.

Tool Overview: FastGPT, Dify, Coze

1. FastGPT

FastGPT is a knowledge base Q&A system based on large language models (LLM) launched by Huanjie Cloud Computing, providing out-of-the-box data processing and model invocation capabilities. Through its Flow visual interface, FastGPT supports workflow orchestration, making the implementation of complex Q&A scenarios simple and efficient.

2. Dify

Dify is an open-source LLM application development platform developed by Suzhou Yuling Artificial Intelligence Technology Company. It combines Backend as a Service and LLMOps concepts, enabling even non-technical personnel to quickly build production-grade generative AI applications.

3. Coze

Coze is an AI chatbot development platform launched by ByteDance, aimed at lowering the barrier for users to build chatbots. Coze provides a Web SDK, allowing users to conveniently embed bots into web applications, expanding its application scenarios.

Feature and Capability Comparison

1. Large Model Integration Capabilities

In terms of large model integration, FastGPT, Dify, and Coze each have their own focus:

FastGPT: Supports most mainstream models, compatible with OneAPI, and niche models can be added through configuration files.

Dify: Offers more model options, with configuration completed directly in the system interface, supporting both OneAPI and Ollama.

Coze: Primarily supports domestic large models such as Doubao and Zhipu, with slightly less flexibility.

工具	支持模型	配置方式	用户体验
FastGPT	主要支持 OpenAI	通过 OneAPI 适配	配置较复杂
Dify	支持 OneAPI、Ollama 等多种模型	系统界面直接配置	体验友好
Coze	支持国内模型豆包和智谱	免配置	模型数量较少

2. Application Publishing Support

In terms of application publishing, the three tools also demonstrate different characteristics:

Both FastGPT and Dify support API calls, multi-browser window preview, and generate multiple API keys.

Coze is suitable for specific platforms, but support for other platforms is somewhat limited, requiring additional time for integration.

工具	浏览器窗口预览	应用嵌入	API 调用	平台友好性
FastGPT	支持	支持	支持	对多平台支持友好
Dify	支持	支持	支持	操作简单，适合新手
Coze	支持	支持	不支持	更适合字节平台，集成不便

3. Chat Functionality

Each platform's design focus for chat functionality configuration is as follows:

FastGPT: Suitable for complex application scenarios, supporting diverse features such as global variables, scheduled execution, and input guidance.

Dify: Simple and automated, supporting automatic prompt generation across multiple large language models, reducing manual input.

Coze: Focuses on conversational experience and personalized memory, enhancing interactive effects through rich dialogue settings.

工具	功能特点	适合场景
FastGPT	全面功能设置，满足复杂需求	复杂应用场景，需自定义的用户
Dify	自动化提示词生成，简化操作	快速部署与开发
Coze	个性化记忆，提升互动体验	对话体验要求高的用户

4. Knowledge Base Functionality

The knowledge base is the core of AI applications, and all three tools have distinct advantages in their knowledge base features:

FastGPT: Supports intelligent training mode, retrieval optimization, etc., suitable for efficient knowledge base construction needs.

Dify: Provides flexible segmentation and indexing settings, suitable for users with specific segmentation requirements.

Coze: Multi-data source support with excellent table and image processing experience, though intelligent annotation effectiveness has slight room for improvement.

工具	初始化知识库构建	文件支持	检索和参数设置
FastGPT	多选索引模型，构建简便	文本、网页	提供丰富检索设置
Dify	支持 Notion 同步和文本导入	文本文件	自定义分段与索引设置
Coze	支持多数据源	文本、表格、图片	丰富检索策略，参数灵活配置

5. Workflow

In terms of workflow application creation and configuration, FastGPT offers rich functionality, suitable for scenarios requiring complex workflows; Dify has clear logic, suitable for lightweight workflows; while Coze is suitable for beginners to get started quickly through simple operations.

工具	工作流创建方式	节点类型丰富度	技术需求
FastGPT	简易应用转换或直接创建	节点多，功能全面	较高
Dify	新建空白应用	逻辑清晰	中等
Coze	添加工作流轻松上手	简单操作快速入门	低

Conclusion

The above Charlii evaluation comprehensively analyzes the core features and application scenarios of FastGPT, Dify, and Coze. FastGPT is suitable for users who need complex functionality and flexible customization, Dify focuses on automation and simple operations, suitable for efficient development scenarios, while Coze emphasizes conversational experience, suitable for users with high requirements for interactivity and personalization. We hope this article helps you choose the most suitable AI knowledge base tool and accelerate the implementation of your AI projects!